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Epidermis Microstructure Inspired Graphene Pressure Sensor with Random Distributed Spinosum for High Sensitivity and Large Linearity Yu Pang,†,# Kunning Zhang,†,# Zhen Yang,† Song Jiang,† Zhenyi Ju,† Yuxing Li,† Xuefeng Wang,† Danyang Wang,† Muqiang Jian,‡ Yingying Zhang,‡ Renrong Liang,*,† He Tian,*,† Yi Yang,*,† and Tian-Ling Ren*,† †
Institute of Microelectronics, Tsinghua University, Beijing, 100084, China Department of Chemistry and Center for Nano and Micro Mechanics (CNMM), Tsinghua University, Beijing, 100084, China
‡
S Supporting Information *
ABSTRACT: Recently, wearable pressure sensors have attracted tremendous attention because of their potential applications in monitoring physiological signals for human healthcare. Sensitivity and linearity are the two most essential parameters for pressure sensors. Although various designed micro/nanostructure morphologies have been introduced, the trade-off between sensitivity and linearity has not been well balanced. Human skin, which contains force receptors in a reticular layer, has a high sensitivity even for large external stimuli. Herein, inspired by the skin epidermis with high-performance force sensing, we have proposed a special surface morphology with spinosum microstructure of random distribution via the combination of an abrasive paper template and reduced graphene oxide. The sensitivity of the graphene pressure sensor with random distribution spinosum (RDS) microstructure is as high as 25.1 kPa−1 in a wide linearity range of 0−2.6 kPa. Our pressure sensor exhibits superior comprehensive properties compared with previous surface-modified pressure sensors. According to simulation and mechanism analyses, the spinosum microstructure and random distribution contribute to the high sensitivity and large linearity range, respectively. In addition, the pressure sensor shows promising potential in detecting human physiological signals, such as heartbeat, respiration, phonation, and human motions of a pushup, arm bending, and walking. The wearable pressure sensor array was further used to detect gait states of supination, neutral, and pronation. The RDS microstructure provides an alternative strategy to improve the performance of pressure sensors and extend their potential applications in monitoring human activities. KEYWORDS: pressure sensor, graphene, flexible device, spinosum microstructure, random distribution
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logical compatibility, the trade-off between sensitivity and linear range remains a huge challenge.11−15 With the development of materials science, advanced materials with different morphologies or microstructures have been widely utilized to fabricate temperature sensors, gas sensors, strain sensors, and pressure sensors.16−23 Particularly, carbon-based materials in the morphology of carbon black,24 carbon tubes,25,26 and graphene27−33 have been used as the sensing elements or conductive fillers in pressure sensors due to
here has been considerable development of wearable, flexible, and stretchable electronic devices for monitoring physiological signals and motion activities in the past decade. This area has exhibited growth in the fitness market reaching $5 billion in 2015.1,2 Continuous measuring and quantifying vital physical signals including body temperature, blood pressure, pulse, and limb movement provides plenty of valuable information for disease diagnoses, therapy, and rehabilitation. The pressure sensor, as an important transducer among mechanical sensors, is of great interest, as revealed by increasing research.3−10 Although significant advancement has been achieved to fabricate pressure sensors with high performance, comfortable attachment, and techno© 2018 American Chemical Society
Received: October 27, 2017 Accepted: January 29, 2018 Published: January 29, 2018 2346
DOI: 10.1021/acsnano.7b07613 ACS Nano 2018, 12, 2346−2354
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Cite This: ACS Nano 2018, 12, 2346−2354
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Figure 1. Bioinspired graphene pressure sensor with an RDS microstructure. (A) Illustration showing the biological microstructure of the human epidermis, and the underlying spinosum of the epidermis layer is a crucial element for high sensitivity. (B) Microscopy of the epidermis showing a spinosum surface and (C) the 3D morphology of abrasive paper turned over shows a similar topography. (D) Fabrication process of the graphene pressure sensor. Photographs (insets) and optical micrographs of the patterned PDMS (E), GO coating on PDMS (F), and after high-temperature reduction (G) using abrasive paper no. 150.
their outstanding electrical and mechanical properties. Moreover, different microstructure or nanostructure geometries (pyramids, 34−39 nanowires, 40−43 hemispheres, 44−46 and prisms47) have been introduced to improve the sensitivity and detectable limitation of planar-structured pressure sensors. For example, Lin and co-workers have reported a self-powered pressure sensor based on a polydimethylsiloxane (PDMS) pyramid microstructure, which exhibits a large linearity range of 0−2.6 kPa but low sensitivity of 0.31 kPa−1.35 Thus, its application in detecting subtle pressure is limited. Another work44 reported a piezoresistive pressure sensor with a high sensitivity of 15.1 kPa−1 using an interlocked hemisphere structure. However, the linear measuring range is only 0−0.5 kPa, which shows a sharp performance degradation for large pressures. Therefore, a pressure sensor with high sensitivity as well as large linearity is beneficial to expand its potential applications. The epidermis that serves as the most important pressure perception tissue in human skin offers an inspired strategy for a bionic structure. The reticular layer of the dermis with a spinosum surface consists of two types of touch/pressure receptors,48 which are extremely sensitive to low-intensity external stimuli. To the best of our knowledge, the spinosum microstructure used in sensor fabrication has not been explored. Bioinspired by the epidermis tissue structure in human skin, we have prepared pressure sensors with bionic spinosum microstructure. Based on the employment of abrasive paper as a template and graphene as a sensing material, a pressure sensor with high sensitivity and large linear range can be achieved. The experimental and theoretical simulation results of the random distribution spinosum (RDS) graphene pressure sensor have been established to explore its working mechanism and high performance. Due to the effective interlocking of RDS layers with a uniform graphene coating, the pressure sensor shows great potential in detecting human physiological signals, voice, and motion activities. It is worth noting that the RDS presents
an alternative strategy to improve other sensor properties, allowing haptic sensing wearable electronics for healthcare and activity monitoring.
RESULTS AND DISCUSSION Nature often offers the inspiration for the advancement of engineering, especially all sorts of bionic structures for artificial electronic devices. Actually, as a tissue overlapped all over the human body surface, skin is a critical element to sense surrounding environmental variations, such as temperature, humidity, and pressure. For instance, the underlying spinosum surface of the dermis that consists of Merkel disks as pressure receptors has a highly sensitive response to the impact of object attachment, as shown in Figure 1A. Due to the fact that the spinosum microstructure can produce a high and local stress concentration at the ridge tips near receptors,49 it plays a major role in afferent stimuli for improved pressure perception. As can be seen from Figure 1B,C, the microscopic structure of human epidermis has a similar topography to that of abrasive paper. Bioinspired by this structure, we used the abrasive paper as a template to prepare the spinosum surface with a random height distribution. Figure 1D shows the fabrication process of the RDS pressure sensor. The PDMS was coated on the abrasive paper to get a micropatterned flexible substrate. After dipcoating the graphene oxide (GO), a high temperature was applied to reduce the GO. Finally, a face-to-face package was used to prepare pressure sensors with different roughness surfaces. The optical image of the micropatterned PDMS substrate using no. 150 abrasive paper is shown in Figure 1E. The morphology of the patterned spinosum PDMS shows smoothly interconnected ridges and dispersive holes, and the low-roughness abrasive papers no. 280, 400, and 600 display a high density of spinosum surface (Figure S1). In order to obtain a uniform GO film with a large area, the surface treatment was performed by oxygen plasma to decrease the contact angle (Figure S2). Figure 1F shows a Claybank color 2347
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Figure 2. Characterization of the prepared RDS samples. (A) 3D morphology of the graphene pressure sensor using abrasive paper no. 600 in the area of 1 × 1 mm2, (B) height profile corresponding to the marked cross profile on the diagonal, (C) probability distribution and cumulative distribution of the height for the SM structure, (D) Raman spectra of the PDMS, GO/PDMS, and rGO/PDMS, (E) SEM image, (F) high-magnification SEM image, and (G) corresponding magnified SEM image of the rGO/PDMS structure using abrasive paper no. 600.
cracks evenly covers the spinosum PDMS surface, which may contribute to the resistance variation. The rGO thickness is about 500 nm, as shown in the magnified SEM image (Figure 2G). The pressure sensor made from an rGO-coated spinosum surface exhibits high sensitivity and large linearity. Figure 3A shows the relative resistance variation versus pressure of the RDS graphene pressure sensor. As we can see, the RDS pressure sensors clearly exhibit two linear resistance segments, a sharp decrease in the low-pressure range and a gradual decrease in the high-pressure range. The sensitivity, which is expressed as (R0 − R)/(R0P), is usually used to evaluate the performance of the pressure sensor, where R0 and R are the initial resistance and resistance under applied pressure, respectively. For the RDS pressure sensor prepared using abrasive paper no. 150− 400, the calculated sensitivity is 25.1 kPa−1 in the range of 0− 2.6 kPa, while it has a value of 0.45 kPa−1 in the high-pressure range. Note that the RDS pressure sensors prepared using abrasive paper no. 150−280 and no. 150−600 have higher sensitivity but narrower linearity range than those of a pressure sensor using no. 150−400. Also, the calculated sensitivities are 30.3 and 27.5 kPa−1 in the pressure range of 0−1.1 and 0−2.1 kPa, respectively. For the high-pressure range, the calculated sensitivities of RDS pressure sensors prepared using abrasive paper no. 150−280 and no. 150-600 are 0.18 and 0.68 kPa−1, respectively. Generally, the trade-off between sensitivity and linearity is necessarily considered for each special application. Namely, a high sensitivity means a low measuring linear range or vice versa. Therefore, the relationship of sensitivity and linearity usually is distributed in the shape of an “L” area, as shown in Figure 3B. It can be clearly seen that compared with other patterned surface pressure sensors the RDS graphene pressure sensor displays an excellent performance with both high sensitivity and a large linear range (Table S1). The working mechanism and simulation will be discussed in detail later to explain the superior properties. We suppose that the high sensitivity in a large linear range is crucial for their extensive applications to detect subtle and medium pressure.
photograph for the GO/PDMS, while a brownish color appears under the microscope, which is also found in low-roughness samples (Figure S3). Note that some deep brownish color areas appear, indicating a thick GO layer located at the bottom surface of dpressions. After a high-temperature reduction, the color of the rGO becomes dark under the microscope, as shown in Figure 1G. The photos of another three rGO/PDMS samples (Figure S4) with low roughness clearly show that uniform graphene has covered the PDMS surface. Figure 2A shows a typical three-dimensional (3D) image of a micropatterned PDMS using abrasive paper no. 600, indicating a nonuniform height distribution within the range of 0−30 μm for the spinosum PDMS (Figure 2B). In addition, the height probability distribution in Figure 2C exhibits a random distribution that is close to a normal distribution with a center height of around 14 μm. The 3D images for the patterned PDMS using abrasive paper no. 150, 280, and 400 (Figure S5) show maximum heights of 120, 60, and 40 μm, respectively. Due to the fixed focus of the microscope, the statistical results of probability distribution in those samples display some degree of distortion for the high-roughness samples. The Raman spectrum of the micropatterned PDMS (Figure 2D) shows that the substrate has three characteristic peaks around 860, 1260, and 1410 cm−1, corresponding to the symmetric rocking, symmetric bend, and asymmetric bend of CH3, respectively.50 After the GO coating, it shows an obvious peak around 1593 cm−1, which belongs to the G-band of graphene. The peak shows a slight red shift to 1600 cm−1 when the GO is reduced at high temperature, which was also observed in previous work.51 Moreover, a subtle peak of the graphene D-band around 1350 cm−1 can be identified because of the overlap of characteristic peaks between PDMS and graphene, revealing little defects or heteroatom doping in the graphene layer. Figure 2E shows the scanning electron microscopy (SEM) image of the rGO/PDMS structure using abrasive paper no. 600. The holes of tens of micrometers are distributed all over the surface, which becomes larger in high-roughness rGO/ PDMS samples (Figure S6). The magnified SEM image in Figure 2F shows that a crumpled graphene layer with some 2348
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Figure 3. Electromechanical properties of the RDS graphene pressure sensors. (A) Relative resistance variation versus the pressure for the pressure sensors using different roughnesses of no. 150−280, 150−400, and 150−600 PDMS substrates. (B) Comparison of the sensitivities within a linear pressure range between an RDS graphene pressure sensor and previous reported surface patterned microstructures. (C) Relative resistance variation of the pressure sensor under the subtle pressure of rice and pushpin loading and unloading. (D) Rise and drop time of the RDS pressure sensor. (E) Relative change in resistance under repeated loading and unloading pressure of 1.5 kPa for 3000 cycles, indicating stability and durability of the pressure sensor.
layers exhibits a sharp decrease for light loading. The contact area would exhibit dramatic enhancement due to the effective interlocking between the low- and high-roughness surface. Therefore, a sharp resistance decrease and a high sensitivity can be obtained, which agrees well with the experimental results within the low-pressure range. Under heavy loading (Figure 4C), the subtle peaks of the RDS contribute to the further decrease of the contact resistance but a slow increase of contact interface and a low sensitivity in the high-pressure range. To understand the resistance variation during the loading process, a circuit model has been postulated to describe the resistance contribution. The total resistance can be calculated as follows:
To investigate the detection limit of the pressure sensors, Figure 3C shows that the pressure sensor can detect subtle pressures of 16 and 35 Pa for rice and a pushpin, respectively. Moreover, the response time of the RDS pressure sensor is shown in Figure 3D. It can be seen that the rise time and drop time are 120 and 80 ms, respectively, indicating a faster resistance signal variation for force unloading than the force loading process. The hysteresis of the response time is mainly attributed to elastic recovery of the PDMS substrate. Besides, the relative resistance variation of the RDS pressure sensor exhibits a high stability and durability under both small (Figure 3E) and large pressure loading (Figure S7). The magnified insets clearly show that there is no obvious degeneration during the whole cyclic process, which is greatly important for longperiod usage. To understand the working mechanism of the RDS graphene pressure sensor, we observed the gap variation between the two layers during the loading process. As shown in Figure 4A, the initial interface of the pressure sensor shows few contacts under the unloading state. Thus, a high initial resistance is obtained for its starting state. We have investigated the interfacial contact status under light and heavy loading. It can be seen from Figure 4B that the gap between the top and bottom rGO/PDMS
R = Rh +
R c1R c2 R c1 + R c2
(1)
where Rh, Rc1, and Rc2 are the resistance in the hole, resistance of contact interfaces, and cracks in the rGO, respectively. The Rh cannot contact another surface during the whole loading process and shows a constant value. Under light loading within tens of micrometers, the Rc1 mainly contributes to the total resistance as a result of the sharp increase of the contact 2349
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Figure 4. Working mechanism of the RDS graphene pressure sensor. Photographs and schematic illustrations of circuit models corresponding to (A) initial state of unloading, (B) light loading, and (C) heavy loading. The pressure distribution of the simulation results for different geometries: (D) pyramid, (E) hemisphere, (F) nanowire, and (G) RDS microstructure at an external loading pressure of 5 kPa. (H) The simulation results of resistance variation versus applied pressure for different surface microstructures.
interface while the Rc2 is neglected. Thus, the equation in the low-pressure range can be simplified as follows: R = R h + R c1
adjacent peaks, indicating a small deformation in the lowpressure range. The simulated results for the four structures under high pressure (Figure S8) show that the RDS exhibits a more homogeneous pressure distribution than those of other three regular morphologies. In order to get quantified results of the sensing performance for different surface shapes, the Matlab model of the resistance variation under pressure loading was established. Based on the discussion above, the enhanced contact area results in more conductive paths for the current with an increasing applied pressure. Also, the contact area changes with the structure compression caused by the pressure. First, the structure models of pyramid, hemisphere, nanowire, and RDS structures are established, by defining a height distribution matrix for each structure. Second, the element of the contact area is selected under different degrees of compression. Each element can be considered as a small resistance, and the total resistance can be considered to be these resistances with a parallel connection. Then we can get the relation of resistance and structure compressing degree for pyramid, hemisphere, nanowire, and RDS structures. By inputting the relation of compressing degree and pressure obtained from the experiment, the relation of resistance and pressure of the four structures is shown in Figure 4H. The RDS pressure sensor exhibits the highest sensitivity and the broadest linearity range among the surface microstructures, which is coincident with the experimental results. On one hand, the pressure sensors with sharp microstructures display a much higher sensitivity compared
(2)
Under heavy loading, Rc1 does not increase dramatically due to the high Poisson ratio of 0.5 for the PDMS substrate.52 The rGO cracks on the micropatterned PDMS surface have a more effective interconnection during a heavy compression, which becomes the main contribution to the further decrease of the resistance. Generally, the sharp structures are beneficial to enhance the sensitivity due to the dramatically increased contact area under a small applied force. However, the sensitivity of the pressure sensor displays a sharp decrease when further deformation takes place, leading to nonlinearity and fast saturation. Considering the comprehensive performance for sensor applications, a high sensitivity within a large linearity range is most desirable. To investigate the pressure distribution for pressure sensors with different surface geometries, we have simulated the pressure distribution under light and heavy applied forces. Figure 4D−G show the pressure distribution after a loading of 5 kPa for pyramid, hemisphere, nanowire, and RDS structures, respectively. As we can see, the pyramid and hemisphere structures have the stress concentration on their top cusp area, while the nanowire displays a homogeneous pressure distribution along the altitude direction. Interestingly, the stress of the RDS structure is concentrated on the initial contact peak and can be transmitted to the root segment of 2350
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Figure 5. Applications of the RDS graphene pressure sensor for various physiological signals’ detection. Photograph of the pressure sensor assembled on (A) a wrist and corresponding signals of the (B) wrist pulse. (C) Photograph of a pressure sensor attached on the human chest area, indicating different signal variations for normal and deep respiration. Photograph of the pressure sensor attached on a (D) loudspeaker and corresponding signals (E) when the word “graphene” was phonated, showing the ability to distinguish U.S. and U.K. pronunciation. (F) Photograph of the sensor put on the heel of the foot and (G) its detected signal when walking, running, and jumping. (H) Illustration of foot states for supination, neutral, and pronation and (I) photograph of pressure sensors fixed on the insole. (J) Schematic diagram of the system design for gait detection. Signals of the pressure array to detect gait states of (K) neutral, (L) supination, and (M) pronation, respectively.
with that of flat microstructures or unstructured sensors due to the rapid enhancement of the contact area in the low-pressure range.36,40 Thus, the spinosum microstructure is beneficial to the high sensitivity of the graphene pressure sensor. On the other hand, the surface-treated microstructure usually can induce a large yield strength and a wide linear range between strain and stress.53 Thus, large deformation and an increased pressure range can be obtained in the RDS microstructure. During the pressure increase, the resistance variation of the uniform distribution with constant contact points is mainly attributed to enhancement of the contact area, which can easily achieve saturation in small deformation and loading force. Although the initial contact points of the random distribution structure first show saturation under a certain pressure, the new contact points inducing a sharply increased contact area can compensate for the whole resistance variation. Therefore, the relative resistance variation still exhibits a linearity within the large pressure range. It can be concluded that the spinosum microstructure with sharp morphology mainly contributes to the high sensitivity, while the random distribution mainly contributes to the large linear range due to its gradual decreasing distribution of spinosum height with the force loading. Owing to the excellent high sensitivity, the RDS pressure sensor exhibits tremendous utility for the detection of human physiological signals, voice, and motion activities. Before the physiological signal detection, we have evaluated the breathability and durability of the graphene pressure sensor. After the
pressure sensor was attached on the volunteer’s arm skin for 2 days, the volunteer felt no obvious discomfort or allergic reaction but a light stamp below the area of the pressure sensor (Figure S9). Moreover, the durability of the RDS graphene pressure sensor has been tested using a steel rod under a pressure of about 200 kPa. After the pressure sensor was impacted 50 times, the reduced graphene layers show no desquamation or damage (Figure S10). The heart rate is the frequency of cardiac cycles induced by the heart muscle contracting and pumping blood from the chambers into the arteries, which is one of the important vital signs and capable of evaluating the physical and mental state of a person. Figure 5A shows a graphene pressure sensor attached on the wrist by medical tape to detect the wrist pulse. It can be seen that the heart rate is clearly measured by the RDS pressure sensor from the radial artery of the wrist (Figure 5B). The pulse can be calculated by the interval between two systolic peaks, showing an interval of 0.85 s and beats per minute of ∼70. Moreover, due to the high sensitivity of the RDS pressure sensor, it exhibits the ability to detect the weak pulse on the finger tips (Figure S11). The magnification of a single peak clearly exhibits the details of the finger pulse conditions, which are the percussion wave (P-wave) and diastolic wave (D-wave), indicating potential applications in vital signal monitoring. Moreover, the RDS graphene pressure sensor exhibits the ability to monitor respiration states. The inset of Figure 5C shows a pressure sensor attached to the human chest area. It can be seen that the person has a normal respiratory rate of 18 2351
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intensity and smooth peaks occur from supination to pronation. However, the intensity of sensor 2 shows a gradual enhancement from neutral to supination and to pronation, indicating a clear transfer of the human barycenter. Although the intensities of sensor 3 have no obvious variation for different gaits, they show entirely different shapes for neutral, supination, and pronation. When comprehensively considering detected signals of both intensity and shape variation, we suppose that the three types of gait states can be distinguished. Moreover, the RDS pressure sensor attached on the palm and brachioradialis shows a signal variation for the human pushup and arm bending (Figure S16), which exhibits great performance to detect the various gross motor movements.
per minute and a clear smooth peak for every time breathing, whereas the intensity displays an enhancement and the signal shape shows a square-like wave for the deep breathing. Interestingly, the flat waveband indicates the maintained time after deep breathing, which is different from other reports with sharp peaks.54,55 It can be concluded that the RDS graphene pressure sensor shows excellent capability for healthcare monitoring of vital signals. In addition, the voice and phonation signals could also be recognized by the RDS pressure sensor. Figure 5D shows a pressure sensor fixed on the Ecoflex surface and put above a loudspeaker. As shown in Figure 5E, we observed that the pressure sensor can exhibit signal distinction for the American pronunciation and British pronunciation of the word “graphene”, as well as the word “sensor” (Figure S12). The magnified image in the inset clearly shows that both pronunciations have two characteristic, subtle peaks, indicating the capability to identify not only different accents but also the stressing of syllables. In addition, the pressure sensor can also be attached on the throat to monitor the muscle movement caused by phonation (Figure S13). The output signals of the pressure sensor exhibit repeatable characteristic peaks for the pronunciation of “graphene” and “sensor”. Both characteristic peaks show subtle peaks for each pronunciation, indicating a high sensitivity for accent identification. The RDS graphene pressure sensor also shows the ability to record sentence signals (Figure S14), indicating good stability and signal feature for different words. In addition, the pressure sensor can also respond to other natural sounds, such as a bird chirp, deer bleat, temple bell, and ceramic peening (Figure S15). Therefore, the RDS graphene pressure sensor has a superior ability for sound and word identification, which shows potential capability in man−machine interactions. Furthermore, the RDS graphene pressure sensor exhibits an excellent ability to detect the huge deformation caused by human motion. Figure 5F shows a pressure sensor attached on the heel by medical tape to detect walking states. As shown in Figure 5G, the pressure sensor displays different signal shapes and intensities for walking, running, and jumping. The normal walking state has a square wave signal response, about one second for each time the foot is lifted and lands, and a walking stride frequency of 60 per minute, whereas for the running state the stride frequency increases up to 120 per minute, and sharp peaks of enhanced signal intensity can be observed. Moreover, the pressure sensor displays a distinguishable response signal for the jumping state. Apart from the impulse peaks for foot landing, the hanging time of about 0.4s can be clearly observed, indicating superior capability to investigate detailed information on walking state recognition. Usually, the human foot gait refers to locomotion achieved through the movement of human walking, which can be altered by neurologic diseases, arthritis, and acquired foot deformities.56 The three typical types of foot gait are shown in Figure 5H, including supination, neutral, and pronation. Because of the stress concentration located on the calcaneus, first metatarsal, and fifth metatarsal, three pressure sensors were fixed on those corresponding sites of the insole for gait detection (Figure 5I). The system design of gait detection is shown in Figure 5J, which mainly consists of a sensor array, microprocessor, and computer for data recording. As seen from Figure 5K−M, the resistance variations show different signal shapes and intensities for the three gait states. For the neutral gait, sensor 1 exhibits the largest resistance change due to human weight mainly acting on the heel, while a decreased
CONCLUSIONS Inspired by the human skin for high-performance haptic sensing, we have fabricated wearable graphene pressure sensors with a combination of spinosum surface microstructure and random height distribution based on an abrasive paper template. These structural designs, materials, and method allow the following advantages: (1) low-cost, easily prepared, and soft/wearable graphene pressure sensors with spinosum structure can be obtained and show a random height distribution compared with previous surface structures; (2) both high sensitivity and large linearity can be achieved simultaneously due to the contribution of the spinosum microstructure and random distribution, respectively; (3) the RDS graphene pressure sensors are promising wearable electronics to detect subtle and large motions for human healthcare monitoring. In summary, we have demonstrated a highly sensitive and large linear range pressure sensor inspired by the skin epidermis. By using abrasive paper as a template and the thermal reduction method, a simple and low-cost fabrication process was presented to prepare an RDS graphene pressure sensor. The height probability distribution of the pressure sensor exhibits a random distribution. The sensitivity of the pressure sensor is as high as 25.1 kPa−1 with a linearity range up to 2.6 kPa. Due to the effective interlocking of the RDS structure between high and low roughness as proved by both experimental and simulation results, the pressure sensor shows an excellent comprehensive performance compared with other patterned surface pressure sensors. The pressure sensor exhibits promising potential in detection of physiological activities, such as human healthcare monitoring, voice, phonation identification, and motion movement. The RDS can be applied in the fabrication of capacitive and piezoelectric pressure sensors, which may contribute to their superior sensing properties. MATERIALS AND METHODS Fabrication of RDS Graphene Pressure Sensors. Commercial abrasive papers with four roughnesses, no. 150, 280, 400, and 600, were utilized as templates. The polydimethylsiloxane (Sylgard 184, Dow Corning) prepolymer was prepared by mixing base silicone gel well with a curing agent in a weight ratio of 10:1. After subjecting the mixture to vacuum for 30 min in a chamber, the mixture was poured on the abrasive paper surface to naturally form a thin film. Then, this was cured on the hot plate at a temperature of 100 °C for 1 h. To enhance the dispersion of GO (XFNANO, Materials Tech CO. Ltd.), the tetrahydrofuran (A.R., Peking Reagent) was added into the GO solution with a volume ratio of 1:5. Before dip-coating the GO layer on the PDMS surface, oxygen plasma treatment was carried out to decrease the contact angle. The peeled and cut PDMS was dipped and dried at 60 °C, and this procedure was repeated three times to get a 2352
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ACS Nano uniform GO layer. Finally, all samples were put in the heating chamber at 200 °C for 2 h to reduce the GO. The obtained samples were cut into rectangular shapes and connected to a copper wire at one end of the pieces with silver paste. The pressure sensor can be fabricated by face-to-face packaging of different roughness rGO/PDMS samples. Characterization of Morphology and Performance of RDS Graphene Pressure Sensors. The morphology and structure of the fabricated sensors were characterized by an optical microscope (Olympus MX61), a 3D imaging system (SENSOFAR AVIT5), and field emission SEM (Quanta 450 FEG, FEI Inc.). Raman spectra were carried out using a laser with a wavelength of 514.5 nm (Lab Ram Infinity Raman). The contact angle was measured with a contact angle analyzer (OCA15Pro, Dataphysics). The loading of applied force was carried out with a testing machine (Shimadzu AGS-X), while the electrical signals of the pressure sensors were recorded at the same time by a digital electrometer (RIGOL DM 3068).
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ASSOCIATED CONTENT
S Supporting Information *
The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsnano.7b07613. Additional information and figures (PDF)
AUTHOR INFORMATION Corresponding Authors
*E-mail: *E-mail: *E-mail: *E-mail:
[email protected].
[email protected].
[email protected].
[email protected].
ORCID
Yu Pang: 0000-0002-6676-0817 Zhen Yang: 0000-0002-8208-1638 Yingying Zhang: 0000-0002-8448-3059 Author Contributions #
Y. Pang and K. Zhang contributed equally to this work.
Notes
The authors declare no competing financial interest.
ACKNOWLEDGMENTS This work was supported by National Key R&D Program (2016YFA0200400, 2016YFA0302300), National Natural Science Foundation (61574083, 61434001), National Basic Research Program (2015CB352101), Special Fund for Agroscientific Research in the Public Interest of China (201303107), and Research Fund from Beijing Innovation Center for Future Chip. The authors are also grateful for the support of the Independent Research Program of Tsinghua University (2014Z01006) and Shenzhen Science and Technology Program (JCYJ20150831192224146). We thank Dr. Yi Zhao at Beijing Tsinghua Changgeng Hospital for his help in observing the microscopy of human skin. REFERENCES (1) Khan, Y.; Ostfeld, A. E.; Lochner, C. M.; Pierre, A.; Airas, A. C. Monitoring of Vital Signs with Flexible and Wearable Medical Devices. Adv. Mater. 2016, 28, 4373−4395. (2) Trung, T. Q.; Lee, N. E. Flexible and Stretchable Physical Sensor Integrated Platforms for Wearable Human-Activity Monitoring and Personal Healthcare. Adv. Mater. 2016, 28, 4338−4372. (3) Dagdeviren, C.; Su, Y.; Joe, P.; Yona, R.; Liu, Y.; Kim, Y.-S.; Huang, Y.; Damadoran, A. R.; Xia, J.; Martin, L. W.; Huang, Y.; Rogers, J. A. Conformable Amplified Lead Zirconate Titanate Sensors with Enhanced Piezoelectric Response for Cutaneous Pressure Monitoring. Nat. Commun. 2014, 5, 4496. 2353
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DOI: 10.1021/acsnano.7b07613 ACS Nano 2018, 12, 2346−2354
